Papers by Xukun Luo
Adaptive Graph Convolutional Network for Knowledge Graph Entity Alignment (2022.findings-emnlp)
Copied to clipboard
| Challenge: | Entity alignment (EA) aims to identify equivalent entities from different Knowledge Graphs (KGs) noisy neighbors of entities transfer invalid information, drown out equivalent information, and ultimately reduce the performance of EA. |
| Approach: | They propose a method to deal with neighbor noises to reduce the performance of EA by capturing the differences and complementarities of multiple KGs. |
| Outcome: | The proposed framework outperforms the state-of-the-art methods in supervised and unsupervised settings. |